To make a decision, we must find out the user's preference, and help the user select an alternative which is the best - according to these preferences. Traditional utility-based decision theory is based on a simplifying assumption that for each two alternatives, a user can always meaningfully decide which of them is preferable. In reality, often, when the alternatives are close, the user is often unable to select one of these alternatives. In this chapter, we show how we can extend the utility-based decision theory to such realistic (interval) cases. © 2014 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Kreinovich, V. (2014). Decision making under interval uncertainty (and beyond). Studies in Computational Intelligence, 502, 163–193. https://doi.org/10.1007/978-3-642-39307-5_8
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